Fundamentos de Python

Resumen

Python is the most popular programming language used for data science and is a must-know to start or advance your career in data. In this course, you will learn the most fundamental skills to write and execute Python code.

We will have an overview of the basic Python concepts, which will enable you to get started with a data science project! You will see how to load, clean, analyze, and transform data with two popular Python packages:

Numpy and Pandas.

Then, we will demonstrate how to effectively communicate the key insights from your analysis by visualizing your data using the Matplotlib and Seaborn packages. Finally, you’ll combine these skills and put your new knowledge into practice by analyzing financial data through a case study.

Upon completing this course, you will be able to:

• Write and execute Python code to create variables, generate outputs, apply various operators, and manipulate different types of data • Capture and transform data using Numpy and Pandas packages • Explore data through different statistical methods to gain a deeper understanding • Visualize data to share insights using the Matplotlib and Seaborn packages • Combine and apply the skills above to analyze financial data This Python Fundamentals course is perfect for anyone who would like to build up their programming skills and use Python for data science to analyze data. This course is designed to equip anyone who desires to begin or further their career in data analysis, quantitative analysis, business intelligence, or other areas of business and finance.

Programa

• Comenzando
En este curso, aprenderemos las habilidades más fundamentales para escribir y ejecutar código en Python. Tendremos una visión general de los conceptos básicos de Python, lo que te permitirá comenzar con un proyecto de ciencia de datos. Veremos cómo cargar, limpiar, analizar y transformar datos con dos paquetes populares de Python: Numpy y Pandas. Luego, demostraremos cómo comunicar efectivamente los insights clave de tu análisis visualizando tus datos utilizando los paquetes Matplotlib y Seaborn. Finalmente, combinarás estas habilidades y pondrás en práctica tu nuevo conocimiento al analizar datos financieros a través de un estudio de caso.
• Conceptos de Python
• Carga y limpieza de datos
• Análisis de datos
• Introducción - Visualización de datos
• Introducción al estudio de caso - Optimización de cartera
• Conclusión del curso
• Evaluación calificada

Impartido por

CFI (Corporate Finance Institute)

Materias

Programming